Protocol for detecting causal variants by co-localizing GWAS and QTL studies using colocRedRibbon

Area of Science:

• Genetics
• Genomics
• Bioinformatics

Background:

• Genome-wide association studies (GWAS) identify genetic variants linked to diseases.
• Expression quantitative trait loci (eQTLs) reveal genetic influences on gene expression.
• Linking these datasets is crucial for understanding disease mechanisms.

Purpose of the Study:

• To present a protocol for co-localizing GWAS SNPs with cis-eQTLs using colocRedRibbon.
• To enable the identification of disease-associated variants influencing gene expression.
• To provide a framework for discovering potential therapeutic targets.

Main Methods:

• Development of the colocRedRibbon protocol.
• Shortlisting relevant GWAS and eQTL variants.
• Computation of co-localization statistics and posterior probabilities.

Main Results:

• The protocol effectively co-localizes GWAS SNPs with cis-eQTLs.
• Co-localized variants offer insights into disease-related gene expression changes.
• Demonstrated applicability to diverse QTL types and GWAS datasets.

Conclusions:

• The colocRedRibbon protocol facilitates the integration of GWAS and eQTL data.
• This integration aids in understanding genetic contributions to disease.
• The method supports the identification of novel therapeutic targets.